20/4/00 p. 1 Postacademic Course on Telecommunications Module-3 Transmission Marc Moonen Lecture-1...

Module-3 Transmission Marc MoonenLecture-1 Introduction K.U.Leuven/ESAT-SISTA

20/4/00p. 1

Postacademic Course on Telecommunications

Module-3 : Transmission

Marc Moonen

Dept. E.E./ESAT, K.U.Leuven

[email protected]

www.esat.kuleuven.ac.be/sista/~moonen/


Module-3 Transmission Marc MoonenLecture-1 Introduction K.U.Leuven-ESAT/SISTA

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Module-3 : Transmission

• Module 1: Introduction to Telecommunications & Networks

• Module 2: Telecommunication Networks and Technologies

• Module 3: Transmission Techniques

• Module 4: Transmission of Sound, Video & Data



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Aims/Scope

• Basic Digital Communication principles

modulation/demodulation, detection (for the regraders/sidegraders)

• New/Advanced Topics

CDMA, multicarrier modulation, smart antennas (for the regraders/upgraders)

• Mostly `bird’s-eye view’ skip mathematical details (if possible)

selection of topics (non-exhaustive)



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New/Advanced Topics?

• Analog & 1G Digital Communication Systems: communication over fairly `simple’ (e.g. AWGN) channels

emphasis on modulation/demodulation/timing/etc... circuitry

• Present Day/Future Communication Systems

= box full of mathematics & signal processing for communication over highly bandwidth constrained

channels, fading channels, etc...



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New/Advanced Topics ?

• Example: Telephone Line Modems

voice-band modems : up to 56kbits/sec in 0..4kHz band

ADSL modems : up to 8Mbits/sec in 30kHz…1MHz band

VDSL modems : up to 52Mbits/sec in …10MHz band

xDSL communication impairments:

channel attenuation/distortion, echo, cross-talk, RFI,...

see Lecture-7/8



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• Example : Wireless Communications Typical spectral efficiency : ...1 bits/sec/Hz

MIMO-transmission (`smart antennas’ & co):

example : V-BLAST (Lucent Techn. 1998)

…40bits/sec/Hz

exploits a `rich scattering environment’

see Lecture-2, Lecture-10



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Enabling Technology is• Signal Processing

1G-SP: analog filters

2G-SP: digital filters, FFT’s, etc.

3G-SP: full of mathematics, linear algebra,

statistics, etc... • VLSI• etc...



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Overview (I)

• 20/4/2000

Lecture-1 : General Intro

Lecture-2 : Limits of Communication• 27/4/2000

Lecture-3 : Transmitter Design/Modulation

Lecture-4 : Receiver Design/Detection• 4/5/2000

Lecture-5 : Channel Equalization

Lecture-6 : Adaptive Equalization



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Overview (II)

• 11/5/2000

Lecture-7 : Multicarrier Modulation (I)

Lecture-8 : Multicarrier Modulation (II)• 18/5/2000

Lecture-9 : Multiple Access/CDMA

Lecture-10: Smart Antennas/MIMO-transmission



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Assignments & Exam

• Assignments

Pen & paper exercises

Self-study material

• Exam 25/5/2000

• WWW-site : telecom.europace.be



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Prerequisites

• Module-1 - M. Goossens : Yes (?)• Module-2 - P. DeMeester : No• Digital Communications Background : No (?)• Mathematics Background : Yes statistics, linear algebra -> see assignments

• Signal Processing Background : Yes digital filters, transforms, stochastic processes

-> see assignments



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Literature

• E.A. Lee & D.G. Messerschmitt

`Digital Communication’ (Kluwer AP 1994)

• J.G. Proakis

`Digital Communications’ (McGraw Hill 1989)

• B. Sklar

`Digital Communications’ (Prentice-Hall 1988)

• S. Haykin

`Communication Systems’ (Wiley 1994)

• H. Meyr, M. Moeneclaey & S. Fechte

`Digital Communication Receivers’ (Wiley 1998)

• etc...



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Acknowledgement

Many of the slides/text/figures/graphs are adopted from the handouts of

Module T2

`Digital Communication Principles’

M.Engels, M. Moeneclaey, G. Van Der Plas

1998 Postgraduate Course on Telecommunications

Special thanks to Prof. Marc Moeneclaey



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Lecture-1 : General Introduction

• Analog vs. Digital Communication• Digital Communication Systems Description

Transmitter

Channel

Receiver• Preview Lectures 2->10



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Analog vs. Digital Communication (I)

Analog Communication:• Transmission of signals that are inherently

analog (speech, video, etc..)• Baseband or passband (AM, FM, ..)• Bandwidth = signal bandwidth

Example: speech signal 0..4kHz -> BW=4kHz• Received signal subject to channel

impairments, transmitter/receiver impairments, etc..



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Analog vs. Digital Communication (II)

Digital Communication:• Transmission of signals that are inherently

digital (`data’) or analog (speech, video, etc..)• Analog signals are converted into digital

signals by sampling & quantization (A-to-D conversion)

Example :

- speech 0…4kHz

- sampled at 8kHz (cfr. Nyquist criterion),

- each sample converted into 8 bits number-> 64kbits/sec

=PCM (pulse code modulation)



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Analog vs. Digital Communication (III)

Digital Communication

• What?

A principle feature of a digital communication system is that during a finite interval of time, it sends a waveform from a finite set of possible waveforms.

The objective of the receiver is not to reproduce the transmitted waveform, but (only) to determine which of the possible waveforms has been sent.



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Analog vs. Digital Communication (IV)

Digital Communication Key Features:• source coding/compression:

Example: speech signal

64kbits/sec-> 11kbits/sec…4kbits/sec

(through `signal modeling’) • channel coding/error correction see also Module-

4• increased spectral efficiency through coding, signal

processing, etc.

Example: v.34 voice-band modem

33.6 kbits/sec in 4kHz voice-band (=8bits/sec/Hz)



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Digital Communication System (I)

• Block Diagram

• Digital Information is digital signal (data) or `sampled+quantized’ analog signal (speech,..)

digital

information s(t) r(t)

digital

information

channelTx Rx

Transmitter with D-to-A

Receiver

with A-to-D

continuous-time

channel



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Digital Communication System (II)

Transmitter • converts bit sequence into waveform s(t)

(=`modulation’)

• bits are grouped into `symbols’

(n bits per symbol, hence M=2^n different symbols)

(=`symbol alphabet’, `constellation’)

• each symbol corresponds to a different waveform segment

• symbol rate = # transmitted symbols/sec = Rs (`Baud rate’, after Baudot, French telegraph engineer)



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Digital Communication System (III)

Channel• physical medium :

twisted pair, coax, optical fiber, radio• channel impairments :

noise, attenuation/distortion, cross-talk,

interference, etc…

)()( tstr



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Digital Communication System (IV)

Receiver

• Converts received signal r(t) into bit sequence

(=`demodulation/detection’)

• Receiver performance :

Bit Error Probability (BEP) or Bit Error Rate (BER)

BER = (#bit errors) / (#transmitted bits)

example : voice : BER <1E-3

data : BER <1E-10



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Transmitter (I)

• Transmitted bits are grouped into symbols (n bits per symbol, hence M=2^n symbols)

• Transmitted symbols are

• Transmitted signal is

where p(t) is transmit pulse, and is symbol energy

( and p(t) are energy-normalized), Ts is symbol period

,....,,, 4321 aaaa Mka ,...,,, 321

sE

ka

k

kss akTtpEts );(.)(



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Transmitter (II)

• Transmitted signal is

• Linear modulation (e.g. PAM, QAM, PSK) all signal segments are proportional to the same pulse p(t)

see Lecture-3 for pulse design

• Non-linear modulation (e.g. FSK)

k

sks kTtpaEts )(..)(

k

kss akTtpEts );(.)(

emphasis on this

see assignments



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Transmitter (III)

• Constellations for linear modulation (=`symbol alphabet’)

PAM PSK QAM pulse amplitude modulation phase-shift keying quadrature amplitude modulation

4-PAM (2bits) 8-PSK (3bits) 16-QAM (4bits)

ps: complex constellations for passband transmission

(see Lecture-3)

IR

II

RR



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Channel (I)

Channel impairments:

• attenuation/distortion (linear/non-linear)• noise (linear/non-linear)• cross-talk (1 or many)• echo (e.g. hybrid impedance mismatch)• RFI (e.g. amateur radio)



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Channel (II)

• Mostly simple linear channel models• Example: AWGN-channel (additive white Gaussian noise channel)

n(t) is zero-mean Gaussian process with power spectrum No/2 for |f|<B (B=bandwidth)

(example: satellite communication channel)

r(t)=Ho.s(t)+n(t)

channel

s(t)

n(t)

Ho +



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Channel (III)

• PS: Gaussian noise model justified through central limit theorem (ex: 1 cross-talker is non-Gaussian, 30 cross-talkers approx. Gaussian)

• PS: `White’ actually means `white within useful bandwidth’ i.o. truly

`white’ (->infinite power hence ill-defined)

• Example: frequency-selective channel

frequency-dependent channel attenuation/phase distortion

(example: twisted pair, coax)

n(t)channel

s(t)

R(f)=H(f).S(f)+N(f)

H(f) +



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Receiver (I)

• Receiver retrieves transmitted symbols

from received signal r(t)

• This leads to an optimization problem

Example: minimum distance receiver

where p’(t) is transmit pulse p(t), modified by channel

,....,, 321 aaa

k

sksaaa dtkTtpaEtr 2,...,, |)('..)(|min321



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Receiver (II)

• For AWGN channels (<->frequency-selective channels), a receiver may consist of :

- (a front-end `(whitened) matched filter’, WMF)

- a symbol-rate sampler (i.e. 1 sample/symbol interval)

- a (memory-less) decision device that decides on the

nearest symbol in the symbol alphabet

• Timing instant for symbol-rate sampling is crucial, hence synchronization scheme needed !

WMF

see

lect

ure 3

-4

r(t)1/Ts

ka



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Receiver (III)

• For frequency-selective channels, the receiver may consist of

- WMF + symbol-rate sampling front-end, or

- anti-alias filtering + Nyquist-rate sampling front-end

followed by more complicated processing: - Maximum-likelihood sequence estimation

(e.g. Viterbi algorithms)

- Equalization + decision device

- …

• See Lecture 4-5



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Preview Lectures 2->10

Lecture-2 : Limits of Communication

• Given a communication channel, an amount of transmit power and transmit bandwidth, what is the maximum achievable transmission bit-rate (bits/sec), for which the bit-error-rate is sufficiently (infinitely) small ?

• Shannon theory (1948)• Recent topic: MIMO-transmission

(e.g. V-BLAST, cfr. supra)



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Lecture-3 : Transmitter Design/Modulation

• Baseband vs passband modulation• Constellations for linear modulation• Transmit pulse p(t) design:

`(root) raised cosine pulses’• Simple receiver structures, eye diagrams, etc.



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Lecture-4 : Receiver Design/Detection

• Inter-symbol interference• Receiver front-ends :

- (whitened) matched filtering + symbol-rate sampling

- anti-alias filtering + Nyquist-rate sampling

• Optimum detection

- MAP/Maximum Likelihood-detection

- MLSE/Viterbi algorithm



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Lecture-5 : Receiver Design/Equalization

• Equalization vs. inter-symbol interference• Equalizer structures :

- Linear equalizers

- Decision-feedback equalizers

- Fractionally spaced equalizers

• Design criteria

- Zero-forcing equalization

- Minimum-mean-squared-error (MMSE) equalization



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Lecture-6 : Adaptive Equalization

• Equalization when channel is unknown and/or time-varying

• Least-mean squares algorithm (Widrow 1965)

- MMSE and stochastic gradient

• Recursive Least Squares algorithms

- Least squares criterion

- Introduction to Fast RLS algorithms



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Lecture-7/8 : Multicarrier Modulation• Applications

- ADSL modems (VDSL modems) • Combination of frequency-shift keying (FSK)

and quadrature amplitude modulation (QAM)• Multicarrier modulation/demodulation based

on fast Fourier transforms IFFT/FFT• Alleviate (?) equalization problem through

usage of cyclic prefix - Time vs. frequency domain equalization



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Lecture-9 : Multiple Access/CDMA• Multiple Access: - TDMA/FDMA (e.g. GSM)

- CDMA (e.g. IS-95, 3G mobile comms)

• CDMA code sequences• CDMA receivers - Single-user detection

- Multi-user detection



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Lecture-10 : Smart Antennas/MIMO transmission• Antenna array receivers - Beamforming

- Channel modeling

• SDMA : `spatial dvision multiple access’ allows different users to use the same frequencies/codes at the same time. Signal separation performed based on spatial properties.

• MIMO-transmission (e.g. V-BLAST)



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Lecture-10 (reserve) : Echo Cancellation

• Echo generation in full-duplex modems - Line echo

- Acoustic echo

• Echo cancellation• Adaptive echo cancellation

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